{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-09T10:49:23.383932Z",
     "start_time": "2020-09-09T10:49:22.966257Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using backend: pytorch\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import dgl\n",
    "import pickle\n",
    "import numpy as np\n",
    "import scipy.sparse as sp\n",
    "import torch as th\n",
    "import torch.nn.functional as F\n",
    "\n",
    "import utils\n",
    "import models\n",
    "import data_loader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-09T10:49:23.395539Z",
     "start_time": "2020-09-09T10:49:23.385205Z"
    }
   },
   "outputs": [],
   "source": [
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = '0'\n",
    "dev = th.device('cuda' if th.cuda.is_available() else 'cpu')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-09T10:49:23.402996Z",
     "start_time": "2020-09-09T10:49:23.396499Z"
    }
   },
   "outputs": [],
   "source": [
    "data_dir = \"../data\"\n",
    "adj_path = os.path.join(data_dir, \"adj_matrix_formal_stage.pkl\")\n",
    "feat_path = os.path.join(data_dir, \"feature_formal_stage.npy\")\n",
    "label_path = os.path.join(data_dir, \"train_labels_formal_stage.npy\")\n",
    "adj_adv_path = os.path.join(data_dir, \"adj_adv.pkl\")\n",
    "feat_adv_path = os.path.join(data_dir, \"features_adv.npy\")\n",
    "model_dir = \"../saved_models\"\n",
    "\n",
    "adj_norm = True\n",
    "feat_denoise = True\n",
    "feat_norm = 'atan'\n",
    "feat_norm_func = utils.feat_norm(feat_norm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-09T10:49:24.883984Z",
     "start_time": "2020-09-09T10:49:23.404051Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finished data loading.\n",
      "NumNodes: 659574\n",
      "NumEdges: 5757154\n",
      "NumFeats: 100\n",
      "NumClasses: 20\n",
      "NumTrainingSamples: 559574\n",
      "NumValidationSamples: 50000\n"
     ]
    }
   ],
   "source": [
    "dataset = data_loader.KddDataset(adj_path, feat_path, label_path)\n",
    "raw_adj = dataset.adj\n",
    "raw_features = dataset.features\n",
    "raw_labels = dataset.labels\n",
    "train_mask = dataset.train_mask\n",
    "val_mask = dataset.val_mask\n",
    "test_mask = dataset.test_mask\n",
    "size_raw, num_features = raw_features.shape \n",
    "test_size = np.sum(test_mask)\n",
    "size_reduced = size_raw - test_size\n",
    "num_class = raw_labels.max() + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-09T10:49:24.887518Z",
     "start_time": "2020-09-09T10:49:24.885037Z"
    }
   },
   "outputs": [],
   "source": [
    "adj_adv = pickle.load(open(os.path.join(data_dir, \"adj_adv.pkl\"), 'rb'))\n",
    "features_adv = np.load(os.path.join(data_dir, \"features_adv.npy\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-09T10:49:24.999139Z",
     "start_time": "2020-09-09T10:49:24.888348Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<660074x660074 sparse matrix of type '<class 'numpy.float64'>'\n",
       "\twith 5843802 stored elements in COOrdinate format>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adj = sp.vstack([raw_adj, adj_adv[:, :size_raw]])\n",
    "adj = sp.hstack([adj, adj_adv.T])\n",
    "adj"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-09T10:49:25.543122Z",
     "start_time": "2020-09-09T10:49:25.000463Z"
    }
   },
   "outputs": [],
   "source": [
    "# adjacent matrix normalization\n",
    "if adj_norm: adj = utils.adj_preprocess(adj)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-09T10:49:26.721489Z",
     "start_time": "2020-09-09T10:49:25.544234Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([660074, 100])\n"
     ]
    }
   ],
   "source": [
    "features = np.concatenate([raw_features, features_adv], axis=0)\n",
    "features = th.FloatTensor(features).to(dev)\n",
    "print(features.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Defense Solution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our defense solution is based on **Feature Denoising**, **Feature Transformation** and **Topology Adaptive GCN**. We show our final solution that satisfies the evaluation requirements of the competition (inference time <10s in a K80 GPU). Some other methods like adjacent matrix denoising (find malicious connections) are also possible. However, for such a large graph, it would take considerable time to do this. Note that in practice, it is difficult to locate attack nodes since one can randomly arange the order of nodes without affecting model's prediction."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 1: Features Denoising\n",
    "\n",
    "Denoise the features by using the statistics of original datasets. Here, we use the min-max values, which is the most efficient one. There are other choices, e.g. using co-occurrence between features to find malicious nodes (useful but more expensive)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-09T10:49:26.745080Z",
     "start_time": "2020-09-09T10:49:26.722584Z"
    }
   },
   "outputs": [],
   "source": [
    "feat_min = -1.73\n",
    "feat_max = 1.62\n",
    "features[th.where(features < feat_min)[0]] = 0\n",
    "features[th.where(features > feat_max)[0]] = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 2: Features Transformation\n",
    "\n",
    "The idea is to map the features into another space to mitigate transfer attacks. It's effective under black-box settings, when attackers have no information about the target model and the defense mechanism. We experimented three options: **Sigmoid**, **Tanh** and **Arctan**. **Arctan** is the most effective one among them. **Attention**: The defender model need to be trained in the presence of feature transformation. And the range after transformation should be in [-1, 1] not [0, 1], the latter will decrease model performance.\n",
    "\n",
    "$$Sigmoid: \\frac{2}{1+e^{-x}}-1 \\in[-1, 1]$$\n",
    "\n",
    "$$Tanh: tanh(x) \\in[-1, 1]$$\n",
    "\n",
    "$$Arctan: \\frac{2\\times arctan(x)}{\\pi} \\in[-1, 1]$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-09T10:49:26.747836Z",
     "start_time": "2020-09-09T10:49:26.745945Z"
    }
   },
   "outputs": [],
   "source": [
    "# Sigmoid\n",
    "# features = 2 / (1 + th.exp(-features)) - 1\n",
    "# Tanh\n",
    "# features = th.tanh(features)\n",
    "# Arctan\n",
    "features = 2 * th.atan(features) / th.Tensor([np.pi]).to(dev)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-09T10:49:28.254302Z",
     "start_time": "2020-09-09T10:49:26.748509Z"
    }
   },
   "outputs": [],
   "source": [
    "graph = dgl.DGLGraph()\n",
    "graph.from_scipy_sparse_matrix(adj)\n",
    "graph.ndata['features'] = features"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 3: Topology Adaptive GCN\n",
    "\n",
    "For the model architecture, we adapt TAGCN [1]. Unlike traditional GCN, TAGCN operates convolutions in vertex domain. For example, in the figure, for node 1, we consider all its 2-hop neighbors, and apply convolution on them. We can also do this for 1-hop or 3-hop neighbors. This convolution can extract important topology information. As shown in this formula, TAGCN can use several trainable weights to learn different scales of topology information.\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "$$X_{i+1}=\\sum_{k=1}^{K}A^kX_iG_{k, i}+\\textbf{1}b_i$$\n",
    "\n",
    "where $X_i \\in R^{N\\times C_i}$, node features at i-th layer; $X_{i+1} \\in R^{N\\times C_{i+1}}$, node features at (i+1)-th layer; $A \\in R^{N\\times N}$, adjacent matrix; $G_{k, i} \\in R^{C_i\\times C_{i+1}}$, learnable weight matrix; $b_i \\in R^{C_{i+1}}$, learnable bias.\n",
    "\n",
    "[1] Du, J., Zhang, S., Wu, G., Moura, J. M., & Kar, S. (2017). Topology adaptive graph convolutional networks. arXiv preprint arXiv:1710.10370."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-10T06:59:18.741714Z",
     "start_time": "2020-09-10T06:59:18.739266Z"
    }
   },
   "outputs": [],
   "source": [
    "# model configuration\n",
    "model_dir = \"../saved_models\"\n",
    "model_name = \"tagcn_atan_128_3.pkl\"\n",
    "num_hidden = 128\n",
    "num_layers = 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-10T06:59:19.279004Z",
     "start_time": "2020-09-10T06:59:19.250989Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TAGCN(\n",
       "  (layers): ModuleList(\n",
       "    (0): TAGConv(\n",
       "      (lin): Linear(in_features=300, out_features=128, bias=True)\n",
       "    )\n",
       "    (1): TAGConv(\n",
       "      (lin): Linear(in_features=384, out_features=128, bias=True)\n",
       "    )\n",
       "    (2): TAGConv(\n",
       "      (lin): Linear(in_features=384, out_features=128, bias=True)\n",
       "    )\n",
       "    (3): TAGConv(\n",
       "      (lin): Linear(in_features=384, out_features=20, bias=True)\n",
       "    )\n",
       "  )\n",
       "  (dropout): Dropout(p=0.0, inplace=False)\n",
       ")"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = models.TAGCN(num_features, num_hidden, num_class, num_layers, activation=F.leaky_relu, dropout=0.0)\n",
    "model_states = th.load(os.path.join(model_dir, model_name), map_location=dev)\n",
    "model.load_state_dict(model_states)\n",
    "model = model.to(dev)\n",
    "model.eval()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# model prediction (unknown test labels)\n",
    "logits = model(graph, features)\n",
    "pred = logits.argmax(1)"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
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